Abstract:
Research on web search has demonstrated the value of using information about the graphical structure of the Web in ranking search results. To date, specific graphical properties have been used in these analyses. We introduce a web projection method that generalizes prior efforts of graphical relationships of the web in several ways. With the approach, we create subgraphs by projecting sets of pages and domains onto the larger web graph, and then use machine learning to construct predictive models that operate on graphical properties. We describe the method and then present experiments that illustrate the construction of predictive models of search result quality and user query reformulation.